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Efficient Design of Distribution Logistics by Using a Model-Based Decision Support System

Authors: J. Becker, R. Arnold


The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structures. Combined with qualitative measures the decision support system will contribute to a more efficient design of distribution logistics.

Keywords: Decision support system distribution logistics, potential analyses, supply chain management.

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[1] Information on Winning+Supply+Chains+Go+Beyond+Cost+and+Service.pdf/b2e78405-a878-485a-921f-99def1d64211
[2] Information on
[3] R. Handfield, F. Straube, H.-C. Pfohl, A. Wieland, Trends and Strategies in Logistics and Supply Chain Management: Embracing Global Logistics Complexity to Drive Market Advantage, DVV Media Group GmbH, Bremen, 2013.
[4] M. Hammer, J. Champy, Reengineering the corporation: A manifesto for business revolution, firstst ed., HarperBusiness, New York, NY, 1993.
[5] R.P. Mohanty, S.G. Deshmukh, Reengineering of a supply chain management system: a case study, Production Planning & Control 11 (2000) 90–104.
[6] J.H. Trienekens, H.-H. Hvolby, Models for supply chain reengineering, Production Planning & Control 12 (2001) 254–264.
[7] J.R. Stock, D.M. Lambert, Strategic logistics management, fourth ed, McGraw-Hill/Irwin, Boston, 2001.
[8] J.D. Müller (Ed.), Delivering tomorrow: Towards sustainable logistics how business innovation and green demand drive a carbon-efficient industry, second. ed, Deutsche Post, Bonn, 2010.
[9] G.N. Evans, D.R. Towill, M.M. Naim, Business process re-engineering the supply chain, Production Planning & Control 6 (1995) 227–237.
[10] P. O'Neill, A.S. Sohal, Business Process Reengineering A review of recent literature, Technovation 19 (1999) 571–581.
[11] M. Al-Mashari, Irani, Zahir, Zairi, Mohamed, Business process reengineering: a survey of international experience, Business Process Management Journal 7 (2001) 437–455.
[12] D.L. Applegate, R.E. Bixby, V. Chvatal, W.J. Cook, The traveling salesman problem: a computational study, Princeton University Press, 2011.
[13] G. Gutin, A.P. Punnen, The traveling salesman problem and its variations, Springer Science & Business Media, 2002.
[14] M. Schmidt, W. Hartmann, P. Nyhuis, Simulation based comparison of safety-stock calculation methods, CIRP Annals - Manufacturing Technology 61 (2012) 403–406.
[15] R.N. Boute, S.M. Disney, M.R. Lambrecht, B. van Houdt, A win–win solution for the bullwhip problem, Production Planning & Control 19 (2008) 702–711.
[16] X. Zhao, F. Lai, T.S. Lee, Evaluation of safety stock methods in multilevel material requirements planning (MRP) systems, Production Planning & Control 12 (2001) 794–803.
[17] G. Campbell, Establishing safety stocks for master production schedules, Production Planning & Control 6 (1995) 404–412.
[18] B.P. Zeigler, H. Praehofer, T.G. Kim, Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems, Academic press, 2000.
[19] R. Bandinelli, M. Rapaccini, M. Tucci, F. Visintin, using simulation for supply chain analysis: reviewing and proposing distributed simulation frameworks, Production Planning & Control 17 (2006) 167–175.
[20] S. Umeda, F. Zhang, Supply chain simulation: generic models and application examples, Production Planning & Control 17 (2006) 155–166.
[21] J.P.C. Kleijnen, Supply chain simulation tools and techniques: a survey, International Journal of Simulation and Process Modelling 1 (2005) 82–89.
[22] M. Goetschalckx, C.J. Vidal, K. Dogan, Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms, European journal of operational research 143 (2002) 1–18.
[23] P. Nyhuis, G. von Cieminski, A. Fischer, K. Feldmann, Applying simulation and analytical models for logistic performance prediction, CIRP Annals-Manufacturing Technology 54 (2005) 417–422.
[24] J. Becker, P. Nyhuis, The Production Logistic Theory as an Integral Part of a Theory of Production Technology, in: C. Brecher (Ed.), Advances in Production Technology, Springer International Publishing, Cham, 2015, pp. 25–36.
[25] P. Nyhuis, H.-P. Wiendahl, Fundamentals of production logistics: Theory, tools and applications, Springer, Berlin, 2009.
[26] P. Fronia, Modellgestützte Potenzialanalyse der Distributionslogistik, PZH-Verlag, Garbsen, 2015.
[27] J. Becker, P. Fronia, P. Nyhuis, A Model-Based Method for Assessing Potentials in Distribution Logistics, Journal of CENTRUM Cathedra: The Business and Economics Research Journal 8 (2015) 45–56.
[28] A.P. Sage, Systems engineering, Wiley, New York, 1992.
[29] P. Nyhuis, C. Wolter, Quantifying the Rationalization Potential in Logistics through Supply Chain Design, Performance Measurement for Increased Competitiveness (2002) 14–23.
[30] H.-P. Wiendahl, J. Reichardt, P. Nyhuis, Handbook Factory Planning 2015.